Intra household Inequality in Low-and Middle Income Countries

Sarah Deschenes, Philippe de Vreyer (), Rozenn Hotte and Sylvie Lambert ()
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Sarah Deschenes: BM = WB - La Banque Mondiale = The World Bank - WBG = GBM - World Bank Group = Groupe Banque Mondiale
Philippe de Vreyer: Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres
Rozenn Hotte: UT - Université de Tours - NEOLAiA - NEOLAiA European University = Université Européenne NEOLAÏA
Sylvie Lambert: PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - ENPC - École nationale des ponts et chaussées - IP Paris - Institut Polytechnique de Paris, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - ENPC - École nationale des ponts et chaussées - IP Paris - Institut Polytechnique de Paris

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Abstract: In low-and middle-income countries (LMICs), unequal sharing of resources within the household has important consequences for poverty measurement and policy targeting. This chapter provides a critical, methodological review of the three main approaches used to measure intra-household inequality, assessing what each can credibly reveal and where its limitations lie. Mortality and anthropometric outcomes reveal marked gender discrimination. Collective household models theoretically allow individual resource shares to be inferred from aggregate household data, but their applicability in LMICs is seriously limited: the assumption of Pareto efficiency rarely holds, owing to bargaining frictions, information asymmetries, and frequent exogenous shocks. Moreover, the resulting estimates of child poverty are often implausibly high relative to that of their parents, raising doubts about the relevance of the identifying assumptions in LMICs contexts.More direct evidence comes from sub-household consumption data, illustrated by the Senegalese Poverty and Family Structure (PSF) survey, which shows that intrahousehold inequality accounts for 14% of total inequality, with more than 13% of poor individuals living in households classified as non-poor. In the complex households typical of LMICs, an individual's position -daughter-in-law, widow, junior co-wife -proves as important as gender in shaping access to resources. We argue that credibly identifying the most vulnerable household members requires moving beyond standard household surveys toward more granular data collection at the individual or sub-household level.

Keywords: Intrahousehold inequality; complex households; gender; individual vulnerability (search for similar items in EconPapers)
Date: 2026-07
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